I am a research scientist at Airbus where I oversee academic research projects, harmonize the autonomous sky vision within standards and regulatory bodies, and lead the technical efforts that cross design, simulation, and product prototypes of autonomous traffic management services. I work across cross-functional teams to create a technology ecosystem that can enable new types of airspace operations that include drone package delivery and autonomous air taxis.
Prior to Airbus, I was a graduate student at Stanford University studying
Artificial Intelligence and Machine Learning.
My research centered around deep
learning and reinfrocement learning. In particular, my interestes were in building algorithms and
computational models that combine perception and automated decision making to create intelligent
robotic systems. The products and projects I work on range from automated traffic managment to autonomous driving to automated surveillance
systems. If you are interested in collaborating either on open-source software or research, feel free to contact me.
Academic and Personal Bio
I was born in Russia and moved to the Bay Area when
I was 10. My Ph.D. path started at Cabrillo Community College where I
studied Physics, Math and Computer Science. I later transferred to UC Berkeley, where I finished
a Physics undergraduate degree. While at Berkeley, I had a deep fascination for the fundamental
nature of our world. To that end, my work at Berkeley focused on creating algorithms that detect
the elusive neutrino particle (while difficult to detect, neutrinos carry a lot of useful
information about how our world works on the most fundamental levels). This work allowed me to
stumble upon Machine Learning and AI, and I became fascinated with building intelligent systems.
I finally ended up a Machine Learning/AI Ph.D. student at Stanford.
I have a cute dog and an indifferent cat. In my spare time, I enjoy hiking, camping,
and bike riding.